6 papers
EVOQUANT: Self-Evolving Verifier-Guided Strategy Optimization for Robust Quantitative Trading
Jie Mao, Changlun Li, Xiang Li +6
Quantitative strategy optimization remains largely manual, requiring domain experts to identify weak signals, tune risk-control rules, and repeatedly validate iterative revisions.…
DeltaLag: Learning Dynamic Lead-Lag Patterns in Financial Markets
Wanyun Zhou, Saizhuo Wang, Mihai Cucuringu +5
The lead-lag effect, where the price movement of one asset systematically precedes that of another, has been widely observed in financial markets and conveys valuable predictive si…
FinKario: Event-Enhanced Automated Construction of Financial Knowledge Graph
Xiang Li, Penglei Sun, Wanyun Zhou +3
Individual investors are significantly outnumbered and disadvantaged in financial markets, overwhelmed by abundant information and lacking professional analysis. Equity research re…
Unleashing Expert Opinion from Social Media for Stock Prediction
Wanyun Zhou, Saizhuo Wang, Xiang Li +3
While stock prediction task traditionally relies on volume-price and fundamental data to predict the return ratio or price movement trend, sentiment factors derived from social med…
The Multi-Round Diagnostic RAG Framework for Emulating Clinical Reasoning
Penglei Sun, Yixiang Chen, Xiang Li +1
In recent years, accurately and quickly deploying medical large language models (LLMs) has become a trend. Among these, retrieval-augmented generation (RAG) has garnered attention…
Automated machine learning for physics-informed convolutional neural networks
Wanyun Zhou, Haoze Song, Xiaowen Chu
Recent advances in deep learning for solving partial differential equations (PDEs) have introduced physics-informed neural networks (PINNs), which integrate machine learning with p…